Data

overview

##        x                y         LOCAL_DATE        TOTAL_PRECIPITATION
##  Min.   :-120.4   Min.   :50.7   Length:26646       Min.   : 0.0000    
##  1st Qu.:-120.4   1st Qu.:50.7   Class :character   1st Qu.: 0.0000    
##  Median :-120.4   Median :50.7   Mode  :character   Median : 0.0000    
##  Mean   :-120.4   Mean   :50.7                      Mean   : 0.7279    
##  3rd Qu.:-120.4   3rd Qu.:50.7                      3rd Qu.: 0.3000    
##  Max.   :-120.4   Max.   :50.7                      Max.   :48.0000    
##                                                     NA's   :106        
##  MAX_TEMPERATURE  MIN_TEMPERATURE     TOTAL_RAIN      MIN_REL_HUMIDITY
##  Min.   :-28.90   Min.   :-37.200   Min.   : 0.0000   Min.   :10.00   
##  1st Qu.:  5.60   1st Qu.: -2.200   1st Qu.: 0.0000   1st Qu.:28.00   
##  Median : 15.00   Median :  3.400   Median : 0.0000   Median :40.00   
##  Mean   : 14.66   Mean   :  3.231   Mean   : 0.5476   Mean   :43.51   
##  3rd Qu.: 23.90   3rd Qu.: 10.000   3rd Qu.: 0.0000   3rd Qu.:59.00   
##  Max.   : 47.30   Max.   : 25.800   Max.   :48.0000   Max.   :97.00   
##  NA's   :51       NA's   :56        NA's   :135       NA's   :13805
##                   x                   y          LOCAL_DATE TOTAL_PRECIPITATION 
##                   0                   0                   0                 106 
##     MAX_TEMPERATURE     MIN_TEMPERATURE          TOTAL_RAIN    MIN_REL_HUMIDITY 
##                  51                  56                 135               13805

check wrangling data

check temp dist for in a random day from all year value

##    [1] 12.8  8.9 11.1  9.4 13.9 13.3 11.1 11.1  7.8 13.3 14.4 16.7 18.9 21.1
##   [15] 15.0  8.3  5.0 12.8 11.7 20.0 15.6 11.7 11.1 11.1 10.6 10.6 11.1 15.6
##   [29]  6.1 12.8  8.9 11.7  9.4 16.1 10.6 11.7 16.1 13.9 13.9 13.9  7.8 11.1
##   [43] 13.9 15.6 14.4 12.8 10.6  8.3 10.6  7.8  3.3 -1.1  6.1 10.0 10.0 10.6
##   [57]  6.7 -2.2 16.1  7.8 10.0 -0.6 -2.8 -6.1  0.0  6.7  7.2  7.2 12.8 15.6
##   [71] 14.4 14.4 10.6 11.1 15.6  7.8 12.2 13.3 12.2 13.3 10.0 11.1 10.0 14.4
##   [85] 12.8 12.8 12.8 15.0 16.1  9.4  9.4 10.0  8.3 13.3 10.6 12.2 12.2 13.3
##   [99] 11.1 16.1 14.4 16.1 11.7 13.9  9.4 15.6 11.1 16.1 16.7 15.6 15.6 13.9
##  [113] 13.9 14.4  7.8 12.2 14.4 14.4 15.6  7.8 15.6  9.4 11.7 14.4 14.4 13.3
##  [127]  9.4 12.8 11.7  8.3 15.6 16.1 15.0 16.1 15.0 18.9 18.3 15.6 18.9 21.1
##  [141] 11.7 17.2 13.3 13.3 12.2 11.1 13.9 20.0 22.8 24.4 11.7 10.6 11.7 13.9
##  [155] 15.0 12.8 16.1 15.0 19.4 16.7 20.0 21.7 19.4 12.2 13.9  6.1  9.4 10.6
##  [169] 10.6 13.3 12.2  8.9 13.3 15.0 16.7 17.8 17.8 20.6 20.6 18.3 22.2 14.4
##  [183]  9.4 13.3 14.4 16.1 17.2 13.3 12.2 10.6  7.2 11.1 13.3 10.6 17.2  8.9
##  [197]  3.3  0.0  3.3  5.6  7.8 11.1 15.6 18.3 18.9 16.7 12.2 13.9 17.8 11.7
##  [211]  4.4  5.0  2.8  2.2  2.2  3.3  1.1 -3.3  8.3 13.9 16.7 11.1 15.0 15.6
##  [225] 17.2  9.4 10.6 12.2 16.1 16.7 19.4 16.1 18.9 21.7 20.0 15.0 20.0 15.6
##  [239] 17.2 20.0 10.6 10.6 13.3 11.1  6.7 10.0 11.1 11.7  8.3  7.8 10.0 13.9
##  [253] 17.8 18.3 11.7 14.4 20.0 14.4 13.3  6.7 12.8 15.0 10.0 12.2 10.6 10.0
##  [267]  8.3 12.2 12.8 15.0 15.0  5.6 11.1 12.8 13.9 12.8 18.3 17.8 16.7 21.1
##  [281] 16.1 14.4 13.3 11.7 17.8 11.1 13.9 17.2 14.4 10.6 12.8 12.2 14.4 11.7
##  [295] 12.8  9.4 15.6 12.8 13.9 15.6  6.1  1.1  7.8 11.7 10.6  3.3  8.9  7.8
##  [309] 13.9  9.4  9.4 12.8 12.8 14.4 12.8 10.0  8.9 13.3 10.0  8.3 13.9 13.3
##  [323] 14.4 18.9 16.1 20.0 13.3  8.9 12.2 10.6  8.3 13.9 15.6 13.3  9.4 12.8
##  [337] 11.7 13.9 13.9 15.6 13.9 14.4 16.1 13.3 20.6 12.8 10.6  9.4 13.3  7.2
##  [351] 13.9 15.0 13.9 11.1 13.9 14.4 10.6 13.9 12.2 13.3  6.7  9.4 10.0  5.6
##  [365]  6.7  5.6  7.2  5.6 11.1  8.3  9.4 10.6 12.2  9.4 11.1 10.6 13.3 10.0
##  [379]  9.4  9.4 11.7 10.6 10.6 11.7 15.0 10.0 11.1 13.3 16.7 14.4 16.0 11.6
##  [393] 13.6 12.4  9.8 14.0  7.7  9.8 12.3 12.1  9.7 10.2  8.4 25.1 23.2 16.2
##  [407] 13.2 12.3 16.2 16.7 16.1 12.2 11.8 14.9 10.6 13.7 14.7 12.4 15.0 13.4
##  [421] 17.5 18.3 18.2 16.6 11.4  9.9  8.0  9.2 10.4  9.0  7.7  9.3 10.6  9.4
##  [435]  9.1 15.7 11.7 10.6 11.3 11.5 11.0 14.5 15.8 11.2 13.5  9.7 15.0 16.0
##  [449] 18.1 17.7 15.9 16.5 13.5 14.7 14.4 17.5 17.3 13.9  9.9 12.4 14.8 14.4
##  [463] 11.9 10.4 10.1 12.5 11.3 15.1 12.4 18.2 12.2  9.0  5.1 10.4 10.9  8.3
##  [477]  9.4 10.8 10.9  9.3 11.9  9.6 13.5 14.4 15.2 16.6 10.6 12.9 11.4 13.9
##  [491] 15.7 12.3 13.4 16.0 17.8 14.0 15.4 14.4 14.8  8.0 12.5 14.5 11.3 14.5
##  [505] 16.7 16.0 18.0 17.5 12.8 15.1 11.0  7.5 10.5 10.5  8.6 10.4 11.2 12.7
##  [519] 11.9  9.5 12.7 21.7 13.1 10.2 12.5 16.0 13.1 14.2  9.5 12.1 15.3 20.4
##  [533] 15.7 13.7 13.4 12.3 12.0 15.6 12.8 15.0 14.5 15.1 15.8 17.2 13.8 11.1
##  [547]  9.6 10.1 15.4 10.9 18.5 22.4 23.3 22.5 17.9 11.7  9.2 13.0 10.8  9.7
##  [561] 10.2  9.0  8.4  9.6 13.3 15.6 18.4 12.0 14.3 11.5 16.0 10.9 12.9 13.2
##  [575]  8.5 13.0 15.3 13.8 14.5 13.5 12.5 10.6 12.7 11.9 12.4 11.6  4.0  8.2
##  [589] 10.5 14.3 14.0 17.3 17.7 17.6 18.7 17.4 18.0 20.6 18.2 19.6 14.1 10.7
##  [603]  7.0 10.3  6.2  8.1 13.9 15.0 14.8 18.8 21.7 19.2 15.0 15.0 16.3 15.4
##  [617] 17.3 18.8 17.4 18.4 16.8 15.0  9.8 15.8 19.3 17.1 23.0 27.5 15.4 14.0
##  [631] 11.1  8.8 10.9 12.7 18.1 20.3 19.4 20.4 22.3 22.2 22.8 22.5 16.5 11.5
##  [645] 12.7 10.0 11.4  7.2  7.3 10.3 13.1 16.5 18.5 17.7 20.7 21.5 15.8 11.8
##  [659] 15.7 15.9 11.9  8.3  5.0  6.9  8.6  7.5  8.6  8.5  6.7  7.6  9.6  9.4
##  [673] 10.2 11.5 14.0 11.1  9.5 13.3  8.7 19.5 15.9 12.7 12.0 14.2 16.9  8.6
##  [687] 12.4 12.1  7.3 11.1 16.3 12.5  7.9 16.3 15.1 13.9  8.8  8.5 13.2  9.1
##  [701] 12.6 14.2 12.2 13.3 18.2 14.8 16.9 15.0 17.9 12.1 10.5  6.6 10.5 11.1
##  [715] 12.3 12.7 15.0 15.6  7.5  9.6 15.8 15.8 11.4 12.2 12.9 16.2 14.9 12.3
##  [729] 13.0 14.6 16.9 20.0 19.4 16.9 13.2 11.8 11.9 13.8 14.2 14.7 13.1  8.3
##  [743] 10.0  9.6 11.3  9.8  9.1 10.6 13.0 17.1 -0.3  7.3 13.7 17.7 16.7 14.7
##  [757]  8.3 13.5 11.6 12.8 17.3  6.4  8.8 14.3 17.5 16.7 16.0 11.2  9.8 13.1
##  [771]  9.5 13.4 14.9 12.3 19.7 16.6 15.6  8.3  9.6  9.4 14.1 19.4 14.6 15.1
##  [785] 14.4 13.7 15.8 16.7 23.3 18.1 12.8 15.7 18.2 21.9 20.6 11.1  6.9  6.5
##  [799] 10.8 14.9 13.5 13.0 13.9 10.2 13.0  8.4 14.9 11.4 15.6 13.3 12.5 15.6
##  [813] 18.6 14.0 13.2 12.0 11.8 11.7 17.4 16.3 13.4 14.7 15.4 13.0 15.1  9.0
##  [827]  5.3 10.8 17.1 12.5 14.5 13.6 13.9 15.2 17.7 14.3  7.5  5.8  9.3  8.7
##  [841] 11.7 11.4 14.6  9.4 10.0  8.2  8.5  6.5 10.4 10.4  8.6  8.7 13.5 15.0
##  [855] 12.2 10.0 12.9 11.3 12.2  8.4 13.9 12.1  8.5 10.4 11.4 11.1  9.3 10.5
##  [869] 10.5 14.2 17.2 14.9 16.3 18.4 15.0 14.7 14.7 16.0 13.4 11.5 12.0 12.4
##  [883]  9.4 13.1 13.3  8.4 12.1 12.9  4.1 10.2 13.1 11.1 15.3 14.3 18.9 13.7
##  [897]  8.6 12.6 13.1 13.8  9.3 10.7 12.5 14.2 15.8 16.7 15.2 14.9 13.0 14.6
##  [911]  8.8  7.9 13.9 18.0 11.7  8.4  6.9  8.0 10.8 13.5 15.6 16.8 17.6 19.1
##  [925] 19.7 21.0 21.8 19.7 17.9 12.7  8.1  4.3  8.2  9.1  8.1  8.5  9.1  9.7
##  [939] 13.8 12.8 11.7 14.2 14.4 13.2 14.4 15.6 14.5 15.5 13.7  7.3 11.6 23.0
##  [953] 18.2 19.7 20.4 11.9 12.6 14.0 12.8 13.1 17.2 15.3 13.4 14.2 13.2 16.0
##  [967] 10.2 15.5 17.5 21.8 22.5 23.1 22.9 21.1 14.6 10.1 14.0  9.2 10.7 14.2
##  [981]  9.9 14.7 14.7 11.5 13.9 14.9 15.3 11.5 12.8 14.9 14.8 13.7  8.6  9.9
##  [995]  9.8  9.8 17.4 13.7 10.5 14.2  8.5  6.9  7.3 10.7 12.5   NA 18.8 18.2
## [1009] 15.6 13.6 14.3   NA 16.9 18.1 17.3 18.9 17.8 18.7  9.9 18.4 15.2 10.8
## [1023] 11.0 10.3  9.6 11.3 13.7 12.7 14.8 12.9  6.9  4.1  6.6  3.9  5.3  9.1
## [1037] 11.9 10.6 12.5   NA  9.3 15.2 14.9  6.8   NA 15.2 18.7 15.1 18.0 10.8
## [1051] 14.8 11.6 20.0 12.5 15.2 14.2 10.9 15.0 17.6 11.0   NA 14.1 15.2 17.1
## [1065] 13.9 15.1 15.8 13.5 10.1 11.0 12.5 12.1 13.0 13.2 16.1  9.3 10.9  9.9
## [1079] 10.6 12.4 14.8 11.7   NA 15.4 16.5 12.2 10.2 14.5 12.5 11.1 14.3 21.6
## [1093] 22.0 13.8 11.0
## [1] 1095

get 90th from the all year for all day value

##   [1]  6.00  6.00  5.80  5.97  6.10  6.10  6.39  6.40  6.60  6.60  6.40  6.60
##  [13]  6.40  6.30  6.31  6.30  6.36  6.41  6.40  6.40  6.50  6.70  6.70  6.96
##  [25]  7.20  7.30  7.50  7.80  7.80  8.30  8.40  8.31  8.30  8.40  8.40  8.70
##  [37]  8.76  8.86  8.90  8.90  8.96  9.00  9.00  9.20  9.40  9.40  9.60  9.70
##  [49] 10.00 10.00 10.30 10.50 10.60 10.60 10.60 10.90 11.10 11.12 11.52 11.70
##  [61] 11.70 12.20 12.50 13.00 13.20 13.50 13.90 14.10 14.39 14.40 14.60 14.80
##  [73] 15.00 15.30 15.50 15.60 15.60 15.80 15.90 16.07 16.10 16.20 16.70 16.90
##  [85] 17.30 17.50 17.80 18.00 18.20 18.40 18.70 18.90 19.30 19.40 19.73 20.00
##  [97] 20.18 20.30 20.54 20.60 20.60 20.82 21.10 21.30 21.50 21.70 21.70 22.00
## [109] 22.33 22.60 22.80 22.80 23.06 23.38 23.60 23.70 23.90 24.40 24.40 24.60
## [121] 25.00 25.52 25.80 26.10 26.20 26.47 26.70 26.70 26.80 27.12 27.50 27.80
## [133] 27.80 27.90 27.90 28.26 28.50 28.60 28.62 28.90 28.90 29.26 29.40 29.40
## [145] 29.40 29.42 29.70 30.00 30.00 30.31 30.56 30.60 30.70 30.70 31.10 31.10
## [157] 31.10 30.71 30.81 31.10 31.10 31.20 31.42 31.66 31.42 31.70 31.70 31.70
## [169] 31.90 32.20 32.20 32.40 32.80 33.04 33.30 33.30 33.50 33.50 33.73 33.73
## [181] 33.68 33.58 33.80 33.90 34.20 34.40 34.40 34.40 34.50 34.50 34.80 34.87
## [193] 34.90 35.00 35.00 35.40 35.50 35.50 35.60 35.60 35.60 36.00 36.00 36.10
## [205] 36.10 36.20 36.20 36.20 36.20 36.13 36.10 36.10 36.10 36.10 36.10 36.10
## [217] 36.05 36.00 35.80 35.60 35.60 35.60 35.50 35.50 35.40 35.36 35.00 35.00
## [229] 35.00 34.70 34.60 34.40 34.20 33.90 33.79 33.50 33.30 33.10 32.80 32.50
## [241] 32.20 32.20 32.20 31.76 31.70 31.40 31.24 31.10 31.00 30.60 30.50 30.40
## [253] 30.27 30.00 30.00 29.60 29.20 28.90 28.80 28.60 28.30 28.30 27.89 27.74
## [265] 27.34 27.10 26.42 26.10 25.70 25.60 25.21 25.00 24.70 24.40 24.30 23.91
## [277] 23.60 23.30 22.80 22.30 21.81 21.30 21.00 20.64 20.60 20.50 20.10 19.90
## [289] 19.40 18.90 18.70 18.30 18.30 17.90 17.80 17.40 17.23 17.00 16.70 16.60
## [301] 16.20 16.10 15.70 15.50 15.28 14.80 14.40 14.20 13.90 13.70 13.40 13.30
## [313] 13.10 12.89 12.80 12.40 12.20 11.90 11.70 11.60 11.40 11.10 11.06 10.80
## [325] 10.60 10.30 10.00  9.90  9.60  9.40  9.40  9.32  8.80  8.46  8.30  8.30
## [337]  8.12  8.00  8.00  7.80  7.80  7.83  7.80  7.80  7.80  7.70  7.55  7.30
## [349]  7.30  7.27  7.20  7.20  7.20  7.20  7.00  6.90  6.70  6.50  6.27  6.10
## [361]  6.10  6.10  6.00  6.00  6.00  6.00

Plot

plot given year temp dist vs baseline 90th

## `summarise()` has grouped output by 'Month'. You can override using the
## `.groups` argument.
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

plot all year temp in grey vs baseline

## Warning: Removed 281 rows containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

Analyze the hw

hw dist for certain 1 year

prepare for the data

## # A tibble: 30 × 7
##    Month   Day Percentile_90 MAX_TEMP_YEAR DayOfYear Condition Cumulative_Count
##    <int> <int>         <dbl>         <dbl>     <dbl> <lgl>                <dbl>
##  1     1     4          5.97          12           4 TRUE                     1
##  2     1     5          6.1            7.6         5 TRUE                     2
##  3     1     6          6.1            8.7         6 TRUE                     3
##  4     1    19          6.4           11          19 TRUE                     1
##  5     1    27          7.5           11.4        27 TRUE                     1
##  6     3    18         15.8           15.9        77 TRUE                     1
##  7     3    19         15.9           16.8        78 TRUE                     2
##  8     3    20         16.1           18.6        79 TRUE                     3
##  9     3    22         16.2           18.8        81 TRUE                     1
## 10     3    23         16.7           18.2        82 TRUE                     2
## # ℹ 20 more rows

plot hw analysis for all year

plot overall count of hw through years

plot for heat map

examine specific year

## Warning: Removed 281 rows containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 281 rows containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).

## Warning: Removed 280 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).